AI generators can now turn a text prompt into polished frames in seconds—an enticing shortcut for directors, previs artists and indie creators who need storyboards yesterday. Midjourney leans into painterly aesthetics, Stable Diffusion rewards tinkerers with deep control, and DALL·E 3 promises natural-language ease inside ChatGPT. Below we compare the three, highlight where each shines, and share a workflow tip: break your script into scene-by-scene prompt ingredients first (Prescene can automate that step) so you spend more time iterating on images and less time copy-pasting slug lines.
Why Use Text-to-Image Storyboards?
- Speed over sketching. A dozen keyframes can materialize in minutes rather than days.
- Cheap ideation. Iterate on lighting, lenses or blocking before hiring an artist.
- Communication. Visuals align crew, financiers and VFX supervisors long before principal photography.
Storyboards are still planning tools; you don’t need pixel-perfect realism, but you do need consistency—the same actor, wardrobe and staging across panels. That’s where each model’s strengths (and quirks) matter.
Midjourney V6
Strengths
- Striking cinematic style out-of-the-box—rich color grading and “art-directed” compositions are its calling card.
- Character & style reference tags.
--creflets you feed a hero image and reuse the same character;--cwcontrols likeness strictness. - Adjustable quality parameter (
--quality 0.25–2). Higher values buy detail, lower values generate faster. - Growing tutorials and prompt recipes for storyboard-specific outputs.
Trade-offs
- Closed ecosystem & Discord UI. No local install or fine-tuned checkpoints.
- Upscaling steps inflate cost compared with free, local diffusion.
- Limited explicit control of depth or masks compared with ControlNet.
When to choose it
- Pitch decks, mood boards, or stylized boards where painterly flair is welcome.
- One-offs rather than long sequential scenes—unless you lean on the reference tags or upload headshots for consistency.
Stable Diffusion (SDXL + ControlNet)
Strengths
| Feature | Benefit for Storyboards |
|---|---|
| Open-source checkpoints | Train a custom model on your cast, sets, even brand palettes. |
| ControlNet / depth / pose conditioning | Lock down camera angles and character positions so panels read like a flip-book. |
| AnimateDiff & Stable Video Diffusion | Turn stills into animatics or camera-move tests. |
| Thriving plugin ecosystem | Tools like Automatic1111, ComfyUI and DreamBooth add batch rendering, tagging, and color-match nodes. |
Trade-offs
- Setup overhead. You’ll juggle GPUs, checkpoints and notebooks—great for pipelines, slower for first-timers.
- Art direction is DIY. Out-of-the-box renders are plainer than Midjourney; you earn quality with model swaps and LoRAs.
- Hardware limits. Consumer GPUs can choke on 4K frames or long inference chains.
When to choose it
- Episodic series or comics where you must lock character-on-model.
- Studios that version-control assets and need reproducible renders.
- Teams comfortable scripting batch jobs—e.g., feed every INT. BRIEFING ROOM – NIGHT scene into an overnight render queue.
DALL·E 3
Strengths
- Integrated with ChatGPT. Write a natural paragraph; ChatGPT rewrites it into a dense prompt automatically.
- Interactive revisions. Ask for “pull back to a medium shot” and get a new frame in the thread.
- Improved language comprehension captures fine-grained scene details (sign text, props, typography).
- One-click “gen_id” lets you reuse subjects for modest character consistency within a session.
Trade-offs
- Session-bound memory. Each image is self-contained, so long storyboards can drift unless re-prompted carefully.
- Tighter safety filters may reject bloody or trademarked frames—plan alternates.
- No local version. You pay per call and rely on cloud latency.
When to choose it
- Writers blocking scenes inside ChatGPT already.
- Quick “what if” thumbnails rather than final production boards.
- Projects with heavy on-screen typography (ads, title cards) where DALL·E outperforms diffusion-based models.
Head-to-Head Snapshot
| Midjourney | Stable Diffusion (SDXL + ControlNet) | DALL·E 3 | |
|---|---|---|---|
| Ease of Use | Discord commands, no install | Local UI; needs GPU setup | ChatGPT chat-style |
| Consistency Tools | --cref, --cw |
ControlNet pose/depth | gen_id session tagging |
| Customization | Limited style refs | Full model training | None |
| Cost | $10–60 /mo tiers | Free (local) + hardware | Pay-per-use via ChatGPT Plus |
| Best For | High-style pitches | Long-form boards, tech teams | Rapid text-heavy frames |
From Script to Prompt: A Structured Workflow
-
Scene Breakdown → Prompt Ingredients
Start with slug line, action line, characters, props, emotional tone, and camera notes.
Prescene can auto-extract these from Final Draft or Fountain files—handy when you have 120 pages to parse and only care about the six hero shots per scene. -
Choose Your Generator
Stylized mood board? → Midjourney
Precise blocking with pose control? → Stable Diffusion + ControlNet
Quick thumbnail via chat? → DALL·E 3 -
Iterate & Upscale
Midjourney’s--quality 2or SDXL’s latent upscaler can bump resolution for print hand-outs. -
Sequence & Annotate
Drop panels back into Prescene.ai’s board view (or your favorite editing tool) to track shot numbers, camera moves and continuity beats.
Prompt-Writing Tips (Model-Agnostic)
- Lead with the camera. “Wide shot, 35 mm lens, slight Dutch angle” roots the AI before you mention the subject.
- Set dressing & lighting next. “Rain-soaked neon alley, practical backlights” yields richer diffusion noise.
- Emotion last. “…heroine clutches backpack, anxious glare.”
- Keep variables stable across panels—swap only what changes shot-to-shot.
If you’re juggling a dozen scenes, run the script through Prescene.ai’s Shot Prompt export so each card already lists location, time-of-day, characters and key props. Then batch-render overnight in your generator of choice—wake up to a first-pass storyboard and start tweaking.
Appendix A – Prompt Templates You Can Copy-Paste
| Goal | Midjourney V6 (Discord) | Stable Diffusion + ControlNet (ComfyUI) | DALL·E 3 (ChatGPT) |
|---|---|---|---|
| Establish a hero shot | /imagine "wide shot, 35 mm, rain-soaked neon alley, heroine in red trench coat, anxious gaze --cref https://imgur.com/hero.jpg --cw 0.6 --ar 16:9 --q 2" |
positive_prompt: wide shot neon alley, heroine red trench coat, anxiouscontrol_type: openposecontrol_image: pose.png |
Prompt to ChatGPT → “Generate a 16×9 storyboard frame of a rain-soaked neon alley. The heroine in a red trench coat looks anxious, medium-wide lens.” Ask: “Use the same woman in all future frames.” |
| Keep the same character for multiple angles | Add --cref plus --cw 0.4 to each prompt for strict likeness. |
Train a LoRA on set photos or use Face ID in DreamBooth; call it in every prompt. | Use the seed/gen_id trick: ask ChatGPT to “regenerate but keep the seed identical.” |
| Batch render an entire scene | Use /describe on your script slug line, then upscale only the finalists to save GPU credits. |
Script a ComfyUI graph that ingests a CSV of scene prompts overnight. | Ask ChatGPT: “For each of these six slug lines, output a separate DALL·E command.” Iterate in-chat, then export images. |
Appendix B – Quick FAQ
How much will Midjourney cost for a 120-frame board?
At ~15 fast GPU minutes per quality 2 render, you’ll use about 30 hours. The Pro tier ($60 /mo) includes 30 fast hours and unlimited Relax time, so one month covers most indie boards.
Can I run Stable Diffusion on a laptop?
Yes—but expect 1–2 minutes per frame on a 6 GB VRAM GPU. For real-time iteration, creators recommend an RTX 4070 Ti (12 GB+) or moving the job to a cloud GPU.
Does DALL·E 3 remember my protagonist across sessions?
Not yet. Character memory resets when the ChatGPT thread closes, so finish a sequence in one sitting or reuse the seed/gen_id parameter manually.
How do I keep hands from melting in Midjourney?
Use --q 2 (or even the experimental --q 4 in v7) for higher fidelity and combine with the --stylize 100 flag; MJ’s May 2025 update improved hand coherence by 30%.
Appendix C – Further Reading & Tools
- Midjourney Docs – Character Reference (
--cref) - Midjourney Docs – Quality Parameter & May 2025 Update
- LinkedIn Deep-Dive on Midjourney V6 Consistency
- Midjourney Pricing Tiers (2025)
- Stable Diffusion Art – AnimateDiff Tutorial
- Hugging Face Papers – Sketch-based Control for Storyboards
- Reddit Hardware Guide – Running SDXL Locally
- Wired – DALL·E 3 Launch & ChatGPT Integration
- OpenAI Community Post – Using Seeds for Consistency
- Reddit Guide – Consistent Characters in DALL·E 3
- Prescene – Scene Breakdown & Scheduling Features
Next Steps
- Draft your prompts today. Take one page of your script, run a free scene breakdown on Prescene, and feed the resulting CSV into your chosen generator.
- Iterate quickly. Lock camera language and character references early; tweak lighting, colors and lenses later.
- Move to animatics. When still frames feel right, pipe them through AnimateDiff or Runway to preview timing and motion.
With a structured pipeline—and a little help from the right AI at each stage—you’ll spend less time wrestling with prompts and more time refining the visual story you set out to tell. Happy boarding!
